Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# YOUR CODE HERE
df = px.data.gapminder()
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
df_2007_new = df_2007_new.reset_index()
fig = px.bar(df_2007_new, y = 'continent', x = 'pop', color = 'continent', orientation = 'h',
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={'continent': ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, text="pop",
title="Continents by population"
)
fig.show()
# YOUR CODE HERE
Add text to each bar that represents the population
# YOUR CODE HERE
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
# YOUR CODE HERE
df_grouped=df.groupby(["continent", "year"]).sum()
df_grouped=df_grouped.reset_index()
fig = px.bar(df_grouped, y = 'continent', x = 'pop', color = 'continent', orientation = 'h', animation_frame="year",
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={'continent': ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, text="pop",
title="Continents by population",
range_x=[0,4000000000]
)
fig.update_yaxes(categoryorder="total ascending")
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
# YOUR CODE HERE
df_country=df.groupby(["country", "year"]).sum()
df_country=df_country.reset_index()
fig = px.bar(df_country, y = 'country', x = 'pop', color = 'country', orientation = 'h', animation_frame="year",
text="pop",
title="Countries by population",
range_x=[0,400000000], #I know, you cannot see India and China, but otherwise you don't see the rest.
)
fig.update_yaxes(categoryorder="total descending")
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
# YOUR CODE HERE
fig = px.bar(df_country, y = 'country', x = 'pop', color = 'country', orientation = 'h', animation_frame="year",
text="pop",
title="Countries by population",
range_x=[0,400000000], #I know, you cannot see India and China, but otherwise you don't see the rest.
height=1000
)
fig.update_yaxes(categoryorder="total descending")
fig.show()
# YOUR CODE HERE
fig = px.bar(df_country, y = 'country', x = 'pop', color = 'country', orientation = 'h', animation_frame="year",
text="pop",
title="Countries by population",
range_x=[0,1400000000],
height=1000
)
fig.update_layout(showlegend=False)
#fig.update_yaxes(range=(131.5,141.5))
#fig.update_yaxes(categoryorder="total ascending")
fig.update_yaxes(range=(9.5, -0.5))
fig.update_yaxes(categoryorder="total descending")
fig.show()